Biomod/2013/Tianjin/Experiments & Results/DeliveryDevice

From OpenWetWare
Jump to: navigation, search

<html> </p> <style>

  • {margin:0;padding:0;font-family:"微软雅黑","Arial";}

body{ width: 960px; height:auto; margin: 0 auto; font-size:12px; font-family:Arial, Helvetica, sans-serif; background-color:#fcfcfc; }


p {margin:0.5em 0 !important; text-decoration:none; font-family:Arial, Helvetica, sans-serif; font-size:12px; }

.logo-section{ height:270px; width:960px; position:relative; margin-top:-10px; float:left; background:url( no-repeat; /*background-color:#0F6;*/ }

.content1{ height:50px; width:960px; position:relative; float:left; /*background-color:#F90;*/ }

.text-box{ width:960px; height:auto; margin-top:0px; float:left; position:relative; /*background-color:#96F;*/ }

.vedio{ width:960px; height:300px; position:relative; float:left; /*background-color:#FCC;*/ }

.link{ margin:0 auto; width:960px; height:100px; text-align:center; /*background-color:#FF6;*/ float:left; }

  1. goTopBtn {POSITION: fixed;TEXT-ALIGN: center;LINE-HEIGHT: 30px;WIDTH: 100px;BOTTOM: 35px;HEIGHT: 100px;FONT-SIZE: 12px;RIGHT: 30px;}
  1. content{margin:0;padding:0;height:1000px;border:0px;}
  1. column-content{background-color:#FFF;

width:960px; height:auto; -moz-box-shadow:0px 0px 15px #000; -webkit-box-shadow:0px 0px 15px #000; box-shadow:0px 0px 15px #000; }

  1. contentSub{background-color:#282828;color:#fff; margin:0;height:30px;padding-top:5px;}
  2. contentSub a{color:#fff;}

/*hidden section*/


  1. sidebar-main{display:none;}
  2. p-cactions{display:none;}
  3. p-personal{display:none;}


<style type="text/css"> .sddm{z-index: 30;width: 960px;height:20px;position:relative;float:left;background-color:#303437;position:raletive;margin-left:0px;} .sddm ul{margin-left:0px;} .sddm li{margin: 0;list-style: none;float: left;font: bold 14px arial;height:20px;background-color:#FFF;border-left:#fff thin solid;border-right:#fff thin solid;} .sddm li a{display: block;margin:0;width: 158px;height:20px;background:#303437;color: #FFF;text-align: center;text-decoration: none;} .sddm li a:hover{background:#999;color:#000;} .sddm div{position: absolute;width:158px;z-index:999;visibility: hidden;margin-top:1px;padding: 0;} .sddm div a{position: relative;display: block;margin: 0;padding: 5px 5px;width: auto;white-space: nowrap;text-align:center;text-decoration: none;color: #FFF;font: 12px arial;height:20px;} .sddm div a:hover{background:#999;color:#000;}

</style> <script type="text/javascript"> var timeout = 500; var closetimer = 0; var ddmenuitem = 0;

function mopen(id) { mcancelclosetime(); if(ddmenuitem) = 'hidden'; ddmenuitem = document.getElementById(id); = 'visible';} function mclose() { if(ddmenuitem) = 'hidden';} function mclosetime() { closetimer = window.setTimeout(mclose, timeout);} function mcancelclosetime() { if(closetimer) { window.clearTimeout(closetimer); closetimer = null;}} document.onclick = mclose; </script>

<style> .photo { width:294px; padding:35px 10px 20px 20px; border:1px solid #BFBFBF; background-color:white; box-shadow:2px 2px 3px #aaaaaa; }

.rotate_left { float:left; -ms-transform:rotate(7deg); -moz-transform:rotate(7deg); -webkit-transform:rotate(7deg); -o-transform:rotate(7deg); transform:rotate(7deg); }

.rotate_right { float:left; -ms-transform:rotate(-8deg); -moz-transform:rotate(-8deg); -webkit-transform:rotate(-8deg); -o-transform:rotate(-8deg); transform:rotate(-8deg); } </style>

<a href="" style="font-size:14px;">Polymerizing</a>

optimize the 1st stem-loop structure & termination

<a href="" style="font-size:14px;">Cleavage</a>

optimize the 2nd stem-loop structure

<a href="" style="font-size:14px;">Delivery device</a>

<img src="" alt="" width="284" height="213" />

To put this track into usage, we construct walkers for this DNA track. We wanted to build a origami with trigger and see if the whole device is goanna work, but the whole project is to complicated and we don’t have instrument’s to characterize it. So we did not do further research or experiments. Instead, we do some modeling work to give it a further accurate prediction.

<style type="text/css"> .box{ width:960px;height:auto; margin:0 auto; overflow:hidden;}

.main{ width:620px; height:auto; float:right;position:relative;padding:30px 30px 10px 10px;font-size:13px;} .fixed{ width:180px; height:400px; font:normal; text-align:center;float:left;word-spacing:0.1em;top:10px;margin-top:10px;} .main img{border:hidden;margin-bottom:5px;} .main div,li,p{font-family:Arial;line-height:150%;word-spacing:0.1em;font-size:13px;}

.box p{color:#000;font-family:Arial, Helvetica, sans-serif;font-size:13px;line-height:150%;text-align:left; clear:both;} .box h1{text-decoration:none;font-weight:normal;color:#000;} .img1{margin:0 150px 15px 150px;padding:5px 5px 5px 5px;background-color:#fafafa;border:thin solid #999; vertical-align:middle;width:400px;} .img1 a{target="_blank";}



  1. toc {

width:260px; margin-left:20px; margin-top:70px; }

.tocbefore { position:absolute; margin-left:20px; }

.tocafter { position:fixed; top:-30px; margin-left:20px; }


<script type="text/javascript"> function getScrollTop() {

   var scrollPos; 
   if (window.pageYOffset) { 
       scrollPos = window.pageYOffset; 
   else if (document.compatMode) { 
   	if(document.compatMode != 'BackCompat')
       	scrollPos = document.documentElement.scrollTop; 
       else if (document.body) 
       	scrollPos = document.body.scrollTop; 
   if(scrollPos < 710){

document.getElementById("toc").className="tocbefore"; } else{ document.getElementById("toc").className="tocafter"; } } window.onscroll=getScrollTop; </script>



  • <a href="#Walker">1 Walker</a>
  • <a href="#Stimulation_about_the_delivery_device">2 Stimulation about the delivery device</a>
  • <a href="#Monte_Carlo_Method_[1]">3 Monte Carlo Method</a>
  • <a href="#Algorithm">4 Algorithm</a>
  • <a href="#Results">5 Results</a>
  • <a href="#MATLAB_Code">6 MATLAB Code</a>
    • <a href="#Code_1">6.1 Code 1</a>
    • <a href="#Code_2">6.2 Code 2</a>
    • <a href="#Code_3">6.3 Code 3</a>



We constructed 2 kinds of walkers, one is a 2-foot one, and the other is a quadruped one. And we think the 2nd one the better one. It meet the shape with the track, which means a better conduction, also it has 4 feet so that the chance of losing the walker will be lower.

Figure 3.3.1 The 2-foot walker.
Figure 3.3.2 The quadruped walker.

Simulation about the delivery device

We abstract the original problem into a simplified 2-dimensional problem. There are two sizes on a plane-a starting site and an ending site. The distance between the two sites is L. A chain starts from the starting site. The chain is composed of a certain number of units, whose length is r. The chains is rotatable to some extent, as shown in Figure 3.3.3. A unit can rotate freely in a certain range of degree. When the ending point of the chain is close enough to the ending site, they can be seen as successfully linked together. To guarantee successful linkage, the number of units of the chain can be too small or too big. When[[Image:#.png]] , the chain can link two site even it is stretched, as shown in Figure 3.3.4. On the contrary, when N is too large, the possibility of successful linkage is also very small.

Figure 3.3.3 The chain is rotatable.
Figure 3.3.4 Simulation Results.
Figure 3.3.5 Simulation Results.

Monte Carlo Method [1]

We adopt Monte Carlo Method to study the influence of number of units, the value of N, on the possibility of successful linkage. And we want to find the optimal solution of N to guarantee linkage of two sites.

Monte Carlo methods (or Monte Carlo experiments) are a broad class of computational algorithms that rely on repeated random sampling to obtain numerical results; i.e., by running simulations many times over in order to calculate those same probabilities heuristically just like actually playing and recording your results in a real casino situation: hence the name. They are often used in physical and mathematical problems and are most suited to be applied when it is impossible to obtain a closed-form expression or infeasible to apply a deterministic algorithm. Monte Carlo methods are mainly used in three distinct problems: optimization, numerical integration and generation of samples from a probability distribution.



Figure 3.3.6 Algorithm Flow Chart.


Figure 3.3.7 The probability of linkage VS number of units.
Figure 3.3.8 One random test when linkage fails.
Figure 3.3.9 An example of successful linkage.


Code 1

function [ next] = rdp( start,r )






Code 2




for ii=2:n




hold on






hold off

Code 3

function [isornot]=randtest(n)






for ii=2:n





if dist<=crit







<a href="#top" title="Top"><img border=0 src=""></a>